Various types of light, present when a digital image is captured, can cause an object in the captured image to have a hue that is not present when the object is viewed directly. For example, various types of artificial light can cause objects in captured images to have an orange hue, while natural light under certain circumstances can cause objects to have a blue hue. This hue is most noticeable on objects within an image that a viewer knows are white and expects to see as white.
To correct this type of image distortion, many sophisticated algorithms are applied to digital images to change pixel values for acquired image data into pixel values that will not show the distortion. This process of changing the values for acquired image data to make portions of an image expected to be white appear white is frequently referred to as adjusting the white balance of the image. White balance algorithms currently known in the art tend to be computationally expensive, and thus unsuitable for being implemented in hardware with real time logic and unsuitable for being implemented on smaller, mobile devices that have limited memory and limited processing power. Many white balance algorithms currently known in the art also require users to supply values for various settings in order for the algorithm to be executed, which undesirably increases a user's involvement in the picture taking process.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.